Kirill Lutcenko

The year is 2040. You’re living under the Anthroogle Protectorate. You’re all out of HumanCoin, and the next drop isn’t until next week, so you’re stuck with Genie 9 sims for now (audiovisual only). It’s okay though, because Claude’s World is streaming tonight. And you love that guy

Definitely feeling it, everyone just hang onto your board. 🏄 justinjackson.ca/claude-code

Now with AI agents running continuously in their loop (like Openclaw), things are getting spicy again. Prompt injections can trigger deep changes in their internals, manipulate their goals, exfiltrate data.

nolanlawson.com/2026/02/07/w...

AI‑Assisted Software Engineering: A Step‑by‑Step Example for Developers Who Don’t Know How to Start So, you are a professional mid- to senior-level developer (if not, this post may not be for you). You know how to write good, effective code and get work done. You hear all the hype around “vibe codin...

Just finished my new article aimed at helping developers who are still struggling to start using AI agents in their day-to-day work. Sometimes all you need is a very concrete, step-by-step example, and I hope this piece can become exactly that.

Sharing is appreciated.

Watching videos titled "X is the best model" is a huge waste of time, now more than ever

Just choose what fits best for your specific problem and get the work done!

In 2026, you don't need to pretend to be a "researcher" to solve business problems in the AI/ML stack: ML models for most problems are already created and implemented, agentic frameworks are written, and LLM vendors offer a variety of models for every use case and budget.

AI/ML departments should be managed not in a “Google Research” style but as development departments with a specialized stack. They should be just another team in the row of other R&D teams like backend, frontend, QA, etc. With narrowly scoped tasks, clear technical requirements, and strict deadlines

In most companies, the picture looks very different from the stakeholders' point of view: they invest in a new technology stack, expect a fast ROI, and want results quickly given the amount they are spending.

The problem is that true research departments are venture investments by definition, and this is a privilege that only huge enterprises can afford: you put some extra cash into hiring PhD grads, give them a wide scope of problems in the hope that, maybe, some of their findings will bring you ROI.

A few thoughts about managing the AI/ML engineering process.

The big problem I see is when group managers of AI/ML departments in small‑mid‑size companies treat their teams as research groups.

Also, I’d be happy to hear how things are going with Lumo. Are you planning to develop this product further, or is the ROI not great and it might be shut down?

The whole Moltbook story perfectly illustrates why I never rush to play with the latest “hot” things. I prefer to wait until early adopters, who seemingly have more free time than I do, figure out whether something is worth investment of my time

Got burning questions about Proton Mail?

Join our AMA on r/ProtonMail tomorrow, February 5th at 11am CET, with our Director of Engineering and Product Lead.

Not on Reddit? We'll pull your best questions from here 👇

Do you have plans to integrate Standard Notes, or at least include it in the paid plan? It feels odd paying for it separately since you've already purchased it.

there's proton wallet for crypto

Thirty percent of my job involves tech leadership, where I dig into existing code and write technical specs for developers, and I use Cursor heavily for it. I can't even imagine how many resources would be needed to develop a tool like this internally.

But will the development and maintenance of this tool be cheaper than a Cursor subscription?

There's another implementation existing in pip, but it's very incorrectly implemented.

GitHub - kirlut/google-adk-mongo-session-service Contribute to kirlut/google-adk-mongo-session-service development by creating an account on GitHub.

Created an extension for the Google ADK library that allows you to save the session state of your agents in MongoDB. For some reason, Google decided not to support Mongo out of the box, so I did it myself.

Written by AI agents and carefully curated by me.

I was just about to publish my very first PyPI package 😢

I like this passage :)

At least they're trying… 🥹

liked it:
"like if we are now linked in a collective mind"

I feel sad seeing that the /llms.txt standard is not widely adopted. I think it's vital for the long‑term adoption of automatic programming, vibe coding, or whatever name you prefer.

We need a way to provide agents with documentation that doesn't rely on web page parsers.

New blog post: Automatic Programming -> antirez.com/news/159